Untitled
building_data = read.csv('data/data_train.csv', header = TRUE)
zipcode_data = read.csv('building-permit-applications-data/zipcode_data_all.csv', header = TRUE)library(tidyverse)## ── Attaching packages ────────────────────────────────────────────────────────────────────────────────────────────── tidyverse 1.3.0 ──## ✔ ggplot2 3.2.1 ✔ purrr 0.3.3
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## ✔ readr 1.3.1 ✔ forcats 0.4.0## ── Conflicts ───────────────────────────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()library(tigris)## To enable
## caching of data, set `options(tigris_use_cache = TRUE)` in your R script or .Rprofile.##
## Attaching package: 'tigris'## The following object is masked from 'package:graphics':
##
## plotlibrary(ggmap)## Google's Terms of Service: https://cloud.google.com/maps-platform/terms/.## Please cite ggmap if you use it! See citation("ggmap") for details.library(zipcode)
data(zipcode)
# SF zipcodes start with 94XXX
zips_sf <- zctas(cb = T, starts_with = c("94"), class = "sf") %>%
select(zip = ZCTA5CE10, geometry)## ZCTAs can take several minutes to download. To cache the data and avoid re-downloading in future R sessions, set `options(tigris_use_cache = TRUE)`##
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|=================================================================| 100%head(zips_sf)## Simple feature collection with 6 features and 1 field
## geometry type: MULTIPOLYGON
## dimension: XY
## bbox: xmin: -122.4299 ymin: 37.35215 xmax: -121.9824 ymax: 37.88476
## epsg (SRID): 4269
## proj4string: +proj=longlat +datum=NAD83 +no_defs
## zip geometry
## 77 94089 MULTIPOLYGON (((-122.0411 3...
## 1287 94111 MULTIPOLYGON (((-122.4057 3...
## 1994 94703 MULTIPOLYGON (((-122.2832 3...
## 2533 94104 MULTIPOLYGON (((-122.4046 3...
## 5055 94086 MULTIPOLYGON (((-122.0581 3...
## 5336 94102 MULTIPOLYGON (((-122.4299 3...register_google(key = 'AIzaSyDZpJXjmmjN23LleD3QYSnkiuDtvluYKcs')
basemap <- get_map(location = c(lon = -122.3999, lat = 37.7846), zoom = 9)## Source : https://maps.googleapis.com/maps/api/staticmap?center=37.7846,-122.3999&zoom=9&size=640x640&scale=2&maptype=terrain&language=en-EN&key=xxxggmap(basemap) +
geom_sf(aes(fill = zip), data = zips_sf, inherit.aes = F, size = 0, alpha = 0.6) +
coord_sf(ndiscr = F) +
theme(legend.position = "none")## Coordinate system already present. Adding new coordinate system, which will replace the existing one.
register_google(key = 'AIzaSyDZpJXjmmjN23LleD3QYSnkiuDtvluYKcs')
basemap <- get_map(location = c(lon = -122.3999, lat = 37.7846), zoom = 12)## Source : https://maps.googleapis.com/maps/api/staticmap?center=37.7846,-122.3999&zoom=12&size=640x640&scale=2&maptype=terrain&language=en-EN&key=xxxzips = zipcode[zipcode$zip %in% building_data$Zipcode, ]
zips$Zipcode = zips$zip
total <- merge(zips, zipcode_data, by="Zipcode")
fin_heatmap <- ggmap(basemap, extent = "device") + stat_summary_2d(data = total, aes(x = longitude, y = latitude, z = Business.total), fun = mean, alpha = 0.6, bins = 30) + scale_fill_gradient(name = "Businesses", low = "green", high = "red")
fin_heatmap
fin_heatmap <- ggmap(basemap, extent = "device") + stat_summary_2d(data = total, aes(x = longitude, y = latitude, z = Restaurant.total), fun = mean, alpha = 0.6, bins = 30) + scale_fill_gradient(name = "Restaurants", low = "green", high = "red")
fin_heatmap
fin_heatmap <- ggmap(basemap, extent = "device") + stat_summary_2d(data = total, aes(x = longitude, y = latitude, z = Fire.total), fun = mean, alpha = 0.6, bins = 30) + scale_fill_gradient(name = "Fires", low = "green", high = "red")
fin_heatmap